Brain Tissue Properties and Morphometry Assessment After Chronic Complete Spinal Cord Injury

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bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Brain tissue properties and morphometry assessment after

chronic complete spinal cord injury

Andreas Hug MD1, Adriano Bernini2, Haili Wang1, Antoine Lutti PhD2, Johann M.E. Jende

MD4, Markus Böttinger MD1, Marc-André Weber MD3,5, Norbert Weidner MD1, and Simone

Lang PhD1

1Spinal Cord Injury Center, Heidelberg University Hospital, Heidelberg, Germany

2Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences

Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland

3Department of Radiology, Heidelberg University Hospital, Heidelberg, Germany

4Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany

5Institute of Diagnostic and Interventional Radiology, University Medical Center Rostock,

Rostock, Germany

Corresponding author: Andreas Hug MD Spinal Cord Injury Center Heidelberg University Hospital Schlierbacher Landstraße 200a 69118 Heidelberg. Germany Phone: +49-6221-5626322 Fax: +49-6221-5626345 Email: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Abstract

There is much controversy about the potential impact of spinal cord injury (SCI) on brain’s

anatomy and function, which is mirrored in the substantial divergence of findings between

animal models and human imaging studies. Given recent advances in quantitative magnetic

resonance imaging (MRI) we sought to tackle the unresolved question about the link between

the presumed injury associated volume differences and underlying brain tissue property

changes in a cohort of chronic complete SCI patients. Using the established computational

anatomy methods of voxel-based morphometry (VBM) and voxel-based quantification (VBQ)

we performed statistical analyses of grey matter volume and parameter maps indicative for

brain’s myelin, iron and free tissue water content in complete SCI patients (n=14) and healthy

individuals (n=14). Our whole-brain analysis showed significant white matter volume loss in

the rostral and dorsal part of the spinal cord consistent with Wallerian degeneration of

proprioceptive axons in the lemniscal tract in SCI subjects, which correlated with spinal cord

atrophy assessed with quantification of the spinal cord cross-sectional area at cervical level.

The latter finding suggests that Wallerian degeneration of the lemniscal tract represents a main

contributor to the observed spinal cord atrophy, which is highly consistent with preclinical

ultrastructural/histological evidence of remote changes in the central nervous system secondary

to SCI. Structural changes in the brain representing remote changes in the course of chronic

SCI could not be confirmed with conventional VBM or VBQ statistical analysis. Whether and

how MRI based brain morphometry and brain tissue property analysis will inform clinical

decision making and clinical trial outcomes in spinal cord medicine remains to be determined.

Introduction

Spinal cord injury (SCI) is a major cause for chronic disability that profoundly affects patients’

autonomy and quality of life. Despite the abundance of empirical evidence on the local effects

of SCI along the spinal cord, our understanding of the concomitant changes in brain anatomy

and function is still limited. Animal models of SCI showed controversial results ranging from

extensive neuronal cell death in cortical areas (Hains et al., 2003) and the rubrospinal tract

(Viscomi and Molinari, 2014) to lack of upper motoneuron degeneration or cell death of

corticospinal neurons (Nielson et al., 2010; Nielson et al., 2011). The lack of in-depth

knowledge about the impact of SCI on brain anatomy in humans highlights the need to provide

in vivo analytic proof of concomitant structural changes that could inform clinical decision

making in respect to treatment and prognosis.

Computational anatomy methods using magnetic resonance imaging (MRI) and

mathematical algorithms to extract relevant brain features allow for statistical analysis of

volume, shape and surface in three dimensional brain space (Ashburner et al., 2003). One of

the well-established methods - voxel-based morphometry (VBM), was used to monitor local

grey matter volume changes following SCI to deliver conflicting results ranging from lack of

SCI related brain anatomy changes (Crawley et al., 2004) to evidence about profound

sensorimotor cortex reorganization (Jurkiewicz et al., 2006; Wrigley et al., 2009a; Henderson

et al., 2011; Freund et al., 2013). More recent reports demonstrate grey matter loss in non-

motor areas including anterior cingulate gyrus, insula, orbitofrontal gyrus, prefrontal cortex and

thalamus (Wrigley et al., 2009b; Grabher et al., 2015; Chen et al., 2017). One of the potential

reasons for the reported controversial findings is the fact that these studies pooled together

patients with incomplete and complete SCI (Crawley et al., 2004; Jurkiewicz et al., 2006; Chen

et al., 2017) not taking into account potential impact of differences in the time span since injury

(Grabher et al., 2015). The non-quantitative character of the used T1-weighted MRI protocols

represents another source for differences between studies. The computer-based estimation of bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

regional volumes and cortical thickness from T1-weighted data is heavily dependent on the MR

contrast, which is influenced by local histological tissue properties that give potentially rise to

spurious morphological changes (Lorio et al., 2016b).

Recent advances in quantitative MRI (qMRI) circumvent these limitations to provide

quantitative maps indicative for myelin, iron and tissue free water content (Helms et al., 2008;

Draganski et al., 2011; Lutti et al., 2014). Investigations applying qMRI restricted to a set of

regions-of-interest reported progressive volume loss in the internal capsule of SCI patients

paralleled by myelin reduction at 12 months post-injury compared to baseline (Freund et al.,

2013). Using the same technique in the very same cohort, the authors observed also myelin

reduction in thalamus, cerebellum and brainstem in the same period of time (Freund et al., 2013;

Grabher et al., 2015). These combined morphometry and tissue property findings in the early

injury phase contrast with the absence of volume differences when comparing sub-acute

(duration <1 year) and chronic (duration >1 year) patients with complete motor SCI (Chen et

al., 2017).

Here we sought to address previous limitations in the field and investigate the sensitivity

of quantitative brain tissue property MRI mapping to detect brain anatomy changes in a

homogenous cohort of chronic complete SCI subjects We used the established voxel-based

quantification (VBQ) and voxel-based morphometry to study potential differences in myelin,

iron and free tissue water content between SCI subjects and healthy controls. We hypothesized

that chronic complete SCI is associated with brain atrophy in the sensorimotor and non-

sensorimotor system paralleled by specific alterations in myelin, iron and water content. bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Materials and Methods

Study participants

All study related procedures were performed after obtaining informed consent according to

protocols approved by the independent local ethics committee. We screened all patients

admitted to the Spinal Cord Injury Center at Heidelberg University Hospital, Germany, for

eligibility participating in the study. The main inclusion criterion was a spinal cord injury grade

(American Spinal Injury Association Scale (AIS) grade A) that dated back at least 3 months

before study participation. The control group was chosen with the intention to minimize age

and gender differences between groups. Clinical scoring and grading were done according to

the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI)

(Kirshblum et al., 2011).

MRI acquisition

All MRI data were acquired on a 3 Tesla scanner (Siemens Verio, Siemens Healthineers,

Germany). The imaging protocol consisted of three whole-brain multi-echo 3D fast low angle

shot (FLASH) acquisitions with predominantly magnetization transfer-weighted (MTw: TR/α

= 24.5ms/6°), proton density-weighted (PDw: TR/α = 24.5ms/6°) and T1-weighted (T1w:

24.5ms/21°) contrast (Helms et al., 2009, 2008; Weiskopf et al., 2013). For each contrast we

acquired multiple gradient echoes with minimum at 2.46ms and equidistant 2.46ms echo

spacing. Per echo 176 sagittal partitions with 1mm isotropic voxel size (field of view and matrix

size 256x240) and alternating readout polarity were acquired. The number of echoes was 7/8/8

for the MTw/PDw/T1w acquisitions to keep the TR value identical for all contrasts. We used

parallel imaging along the phase-encoding direction (acceleration factor 2 with GRAPPA

reconstruction) (Griswold et al., 2002) and partial Fourier (factor 6/8) along the partition

direction. bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Map calculation

The R2*, MT, PD* and R1 quantitative maps were calculated as previously described

(Draganski et al., 2011). For map calculation we used in-house software running under SPM12

(Wellcome Trust Centre for Neuroimaging, London, UK; www.fil.ion.ucl.ac.uk/spm) and

Matlab 7.11 (Mathworks, Sherborn, MA, USA). R2* maps were estimated from the regression

of the log-signal of the eight PD-weighted echoes. MT and R1 maps were created using the

MTw, PDw and T1w data averaged across all echoes (Helms et al., 2008). All maps were

corrected for local RF transmit field inhomogeneities using the inhomogeneity correction

UNICORT algorithm in the framework of SPM (Weiskopf et al., 2011).

Voxel-based morphometry (VBM) and voxel-based quantification (VBQ)

For automated tissue classification in grey matter (GM), white matter (WM) and cerebrospinal

fluid (CSF) we used the MT maps within SPMs “unified segmentation” approach (Ashburner

and Friston, 2005) with default settings and enhanced tissue probability maps (Lorio et al.,

2016a) that provide optimal delineation of subcortical structures. Aiming at optimal anatomical

precision, we estimated subject specific spatial registration parameters using the diffeomorphic

algorithm based on exponentiated lie algebra - DARTEL (Ashburner, 2007). For VBM analysis,

we scaled the probability maps with the corresponding Jacobian determinants to preserve the

initial total amount of signal intensity. For VBQ analysis, we followed the same strategy by

applying a weighted averaging procedure that ensures the preservation of the initial signal

intensity of the MT, PD* and R2* parameter maps (Draganski et al., 2011). The resulting maps

were spatially smoothed using an isotropic Gaussian convolution kernel of 8 mm full-width-at-

half-maximum. bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Spinal cord cross-sectional area (CSA) assessment

For CSA assessment we used the calculated T1-weighted images after contrast adjustment

within snap-ITK (Yushkevich et al., 2006). Delineation of spinal cord was performed by

outlining the spinal cord circumference manually (AH) at the C2/3 level slice by slice in the

axial plane yielding a total of 15 continuous slices. For an approximation of the mean cross-

sectional area of the upper spinal cord the average of these 15 slices was used.

Statistical analysis

We used parametric and nonparametric statistics from the software package JMP® - v12, for

descriptive analysis of clinical data where deemed appropriate.

We created voxel-based parametric regression models with the group factor (SCI x healthy

controls) as main predictor variable, and age, total intracranial volume (TIV - sum of GM, WM,

and CSF tissue classes) and gender as additional variables (Barnes et al., 2010) in an unpaired

two-sample t-test design as implemented in SPM12. For the whole-brain analysis we reduced

the search volume within brain’s GM or WM yielding 10 separate models (2 for VBM – GM-

VBM and WM-VBM, 8 for VBQ - GM-PD*, GM-MT, GM-R1, GM-R2*, WM-PD*, WM-

MT, WM-R1, WM-R2*). Parameter estimates and beta weights were estimated by appropriate

one-sided t-contrast statements with corresponding statistical parametric T-maps. To control

for multiple comparisons in this voxel-based analysis, family-wise error (FWE) correction

methods using Random Field Theory were applied. The peak level height threshold for

statistical significance was set at FWE p<0.05 with no cluster extent threshold.

Results

Population characteristics

MRI scans were obtained during a sampling period of 3.5 years. The main clinical

characteristics of the patient population are summarized in table 1. We recruited 14 patients and

14 control subjects. The mean age in the control and patient group were 46±16 and 55±13 years

(p=0.1147), respectively. The female male ratio was 3:11 in each group (p=1.0). The median

time since SCI was 144 (14-568) months. Lesion severity in all patients was sensorimotor

complete (AIS grade A). The TIV in the healthy control cohort was 1571±171ml (mean ± SD)

and 1479±210ml (mean ± SD) - in SCI subjects (p=0.2169).

VBM and VBQ analysis

In the whole-brain VBM analysis we observed WM volume decreases in the dorsal part of the

rostral cervical spinal cord in SCI subjects compared to healthy controls (mean difference 10±2

µl). There were no other significant grey or white matter brain volume differences (table 2; fig.

1).

The cross-sectional area (CSA) analysis at the cervical level revealed smaller CSA in SCI

subjects compared to controls (60.2±8.1 mm2 versus 74.5±10.4, p<0.001). We found a positive

correlation between the loss of cervical level CSA and WM volume at MNI -2 -48 -68 (r=0.662;

p<0.001). CSA was not associated with any other WM and GM brain volume changes.

The VBQ analysis did not reveal any significant between-group differences.

Discussion

In this study, we identified WM volume loss (approximately 10 µl) in the most rostral and

dorsal part of the spinal cord in chronic sensorimotor complete SCI subjects. This volume loss

correlated positively with spinal cord atrophy at the cervical level. In contrast to published

results despite a reasonable sample size and a highly homogenous population from clinical and

pathophysiological point of view, we were not able to find any morphometry or brain tissue

property differences in SCI patients that reached the accepted levels of statistical significance.

The reduced volume in the dorsal region of the rostral spinal cord in SCI subjects most

likely reflects Wallerian degeneration of large proprioceptive sensory axons, which has been

confirmed histologically (Becerra et al., 1995; Weber et al., 2006). It is unlikely that the volume

change at the rostral spinal cord was generated by a software algorithm induced imaging artifact

due to false classification/registration (Bookstein, 2001). Quality inspection of the normalized

images after application of the DARTEL algorithm did not indicate false classification or

registration. The close positive correlation between spinal cord cross sectional area at the C2/3

level and the WM volume at the uppermost part of the spinal cord also supports the hypothesis

of a true biological effect. Cord atrophy at the cervical and medulla oblongata level is a

consistent finding after SCI, which is associated with more severe disability (Freund et al.,

2010; Freund et al., 2011; Freund et al., 2013). In other neurological diseases such as

Parkinson’s disease volume changes were confirmed in similar regions (Jubault et al., 2009).

WM volume reductions in the brain stem topographically related to the corticospinal tract

and in the left cerebellar peduncle have been previously described in a more heterogeneous

(more incomplete SCI subjects) and less chronic cohort of SCI subjects (Freund et al., 2011;

Freund et al., 2013). However, volume changes in respective neuroanatomical regions were not

reproducible in our more homogeneous chronic SCI cohort. Volume reductions in our cohort

were located more caudal in the most rostrocaudal region of the cervical spinal cord consistent

with the localization of the dorsal funiculus. Whether degenerative changes such as retrograde bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

axon dieback or neuronal atrophy/cell death occur in corticospinal projections as suggested by

VBM studies (Freund et al., 2011; Freund et al., 2013) is still debated. However, most recent

preclinical studies indicate that respective alterations in the corticospinal tract – at least in

rodents – cannot be observed (Nielson et al., 2010; Nielson et al., 2011). Remote changes in

the brain related to neurogenesis or gliogenesis, which also could have produced volumetric

changes in VBM studies (Killgore et al., 2013), were not observed in animal models of SCI

(Franz et al., 2014). Post-mortem histological data from human SCI subjects are not available

to either confirm or reject such changes.

Previous studies reported inconsistencies in respect to MRI based volumetric changes in

the brain and affected regions in the brain (Crawley et al., 2004; Jurkiewicz et al., 2006;

Wrigley et al., 2009a; Freund et al., 2011; Freund et al., 2013; Hou et al., 2014). In the current

study, we were not able to attribute any VBM or VBQ brain or brainstem differences

unambiguously to chronic sensorimotor complete SCI. The median time since injury was

around 12 years in the analyzed cohort. Only one other study (Wrigley et al., 2009a) analyzed

a comparable SCI group in respect to injury severity and time since injury. However, our data

do not support their finding of extensive reduced GM volumes in motor and non-motor regions

of the brain related to SCI. We identified a correlation of brain volume reductions in respective

regions only related to age (statistical significant covariate associated with smaller GM

volumes; used as nuisance variable in our study), which has been consistently shown in

previous studies not related to SCI (Raz et al., 2007; Thompson and Apostolova, 2007;

Draganski et al., 2011). Lack of statistical power is also unlikely to explain the deviating

findings. 14 SCI subjects were investigated in the present study, whereas 13 (Freund et al.,

2013), 10 (Freund et al., 2011), 15 (Wrigley et al., 2009a), and 17 (Jurkiewicz et al., 2006) SCI

subjects were enrolled in previous MRI studies.

In summary, our VBM and VBQ analyses in a highly homogenous group of chronic SCI

subjects failed to detect main effects of chronic complete SCI on brain’s anatomy. These bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

findings corroborate the absence of strong preclinical evidence of secondary neurodegenerative

remote changes in the brain, yet confirm histological evidence in respect to remote changes in

the spinal cord. At least with the methodology employed in the current study the application of

MRI technology is not able to detect suitable and clinically meaningful markers in the brain,

which help facilitate clinical decision making or enrich innovative clinical trial designs. bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Acknowledgements

This study was supported by grants from the Deutsche Forschungsgemeinschaft (SFB1158) to

Norbert Weidner and rom the Medical Faculty Heidelberg to Andreas Hug. We thank Bogdan

Draganski from the Department of Clinical Neurosciences Lausanne University Hospital,

University of Lausanne, Switzerland, for his expert advice.

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Table 1: Characteristics of SCI subjects. AIS (American Spinal Injury Association Impairment

Scale), NLI (Neurological Level of Injury)

ID AIS NLI Age Duration (years) (months) P1 A C7 66 531 P2 A T7 62 519 P3 A T10 32 206 P4 A T5 59 122 P5 A T3 55 114 P17 A C5 21 7 P19 A T5 59 4 P20 A T8 65 4 P21 A T6 61 66 P22 A C6 53 16 P25 A C3 52 385 P30 A C6 65 568 P32 A T9 62 567 P34 A T5 58 165

Table 2: Voxel based morphometry significant findings (p<0.05 after FWE); WM = white

matter; KE = cluster extent; T = t statistic; Z = z score statistic; coordinates = coordinates in

Montreal Neurological Institute (MNI) space.

tissue contrast regions p FWE- KE T Z coordinates map corrected x y z

WM SCI

Figure legends

Figure 1:

For illustration purposes representative section planes with significant voxels in VBM analysis

at the alpha<0.001 uncorrected statistical threshold level are depicted. Color-coded voxels

depict reduced WM volume in SCI subjects compared to healthy control individuals. The color

scale represents T-values (height threshold: T=5.21, p=0.05 FWE) bioRxiv preprint doi: https://doi.org/10.1101/547620; this version posted February 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Figure 1